Data synchronization method and system based on electronic cloud film and report

Abstract

The invention discloses a data synchronization method and system based on an electronic cloud film and a report, and relates to the technical field of data synchronization, and the method comprises the steps: firstly storing patient information data, then collecting and preprocessing image, dust and bar code data in real time, then carrying out the comprehensive calculation to obtain a scanning abnormal factor, and judging whether the scanning is normal or not according to the scanning abnormal factor; if normal, directly matching the data to obtain a result, and if abnormal, restoring the identity of the patient through an algorithm and matching to obtain a result. Through multi-source data collection and calculation, dust interference is accurately recognized, a multi-source matching algorithm is triggered to restore the identity of a patient when abnormity occurs, manual input is avoided, the data synchronization time is shortened, the patient acquisition efficiency is improved, two types of sensors cooperate, an evaluation model is constructed by means of multiple parameters, and the evaluation efficiency is improved. When abnormal, identity is repaired through image contour and bar code dual verification, the data synchronization success rate under dust interference is improved, and the problem of matching errors is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data synchronization, and in particular to a data synchronization method and system based on electronic cloud films and reports. Background Art

[0002] After the patient completes examinations such as CT or MRI, the imaging data generated by the medical equipment and the diagnostic report reviewed by the doctor are synchronized to the cloud in real time through the system, ensuring that the electronic cloud film and report form a uniquely bound digital file in the cloud. When the patient scans the examination form barcode on the self-service examination machine, the device retrieves the synchronized electronic cloud film and report from the cloud through identity authentication, and displays high-definition images and detailed diagnostic content in graphic form, thereby realizing synchronous data connection.

[0003] For example, the invention patent with publication number CN119182782B discloses a data synchronization system and method based on electronic cloud film and report, which includes the following steps: for emergency scenarios, configure a real-time synchronization strategy; for non-emergency scenarios, configure a periodic synchronization strategy, and provide a manual synchronization strategy function; calculate the synchronization delay index of all synchronization strategies through the synchronization log and performance indicator data of each synchronization strategy; compare the data transmission volume of each synchronization task with the benchmark data volume to obtain the synchronization data volume index; calculate the synchronization frequency index through the average synchronization period, average synchronization delay and synchronization success rate; calculate the synchronization demand index by combining the synchronization delay index, synchronization data volume index and synchronization frequency index; compare the synchronization demand index with the synchronization demand threshold; take corresponding measures according to the comparison results, and realize accurate identification and differentiated processing of personalized needs.

[0004] However, the above patent does not take into account that when dust appears on the scanner of the self-service examination machine, the visible red light of the scanner may cause abnormalities in scanning the barcode of the patient examination form, and the patient's information may not be scanned, resulting in the patient's information being unable to be synchronized with the data of the electronic cloud film and report. As a result, the patient has to manually enter his or her identity information and confirm whether the input is correct each time, thereby extending the synchronization time of the patient's identity information with the electronic cloud film and report data, resulting in low efficiency for patients to obtain electronic cloud films and reports. Summary of the Invention

[0005] Technical problems solved

[0006] In response to the shortcomings of the existing technology, the present invention provides a data synchronization method and system based on electronic cloud film and reports, which solves the problem that dust accumulation on the self-service examination machine scanner causes abnormal red light scanning barcodes, thereby blocking its data synchronization with the electronic cloud film and report due to the inability to read patient information, forcing patients to manually enter and confirm their identity information, prolonging data synchronization time and reducing the efficiency of patients in obtaining electronic cloud films and reports.

[0007] Technical Solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a data synchronization method and system based on electronic cloud film and report, comprising the following specific steps: step one: storing patient information data; step two: starting real-time collection of image data, dust data and barcode data; step three: preprocessing the image data, dust data and barcode data; step four: performing comprehensive calculation on the preprocessed image data, dust data and barcode data to obtain a scanning abnormality factor, and analyzing whether the scanning is abnormal based on the scanning abnormality factor. If the scanning is normal, the barcode data is matched with the patient information data to obtain an electronic cloud film and report, and the process is terminated. If the scanning is abnormal, the image data and barcode data are comprehensively calculated through a data multi-source matching algorithm to obtain patient identity repair data, which restores the patient's true identity information. Then, the patient identity repair data is matched with the patient information data to obtain an electronic cloud film and report, and the process is terminated.

[0009] Furthermore, the specific method of analyzing whether the scan is abnormal based on the scan abnormality factor is as follows: setting a scan abnormality threshold, comparing the scan abnormality factor with the scan abnormality threshold, if the scan abnormality factor is less than or equal to the scan abnormality threshold, then the scan is analyzed to be normal; if the scan abnormality factor is greater than the scan abnormality threshold, then the scan is analyzed to be abnormal.

[0010] Furthermore, the specific method for obtaining the scanning abnormality factor is as follows: the image data is processed by an image contour segmentation algorithm and an image contour tracking algorithm to obtain an image contour, normalization processing is performed based on the image contour, dust data, and barcode data, and comprehensive calculation is performed to obtain dust influence parameters and scanning state parameters, normalization processing is performed based on the dust influence parameters and the scanning state parameters, and comprehensive calculation is performed to obtain a scanning abnormality factor; SY = (HC + k) × MC; wherein SY represents the scanning abnormality factor, HC represents the dust influence parameter, MC represents the scanning state parameter, and k represents a positive real number.

[0011] Furthermore, the specific method for obtaining the dust impact parameter is as follows: setting the dust participation value according to the number of image contours, the dust data includes the current amplitude and the current amplitude quantity, and the barcode data includes the voltage amplitude and the voltage amplitude quantity. According to the change of the current amplitude in the time series, the current attenuation accumulation value is obtained, and the current fluctuation value is obtained by the variance method and calculation based on the current amplitude and the current amplitude quantity. The dust impact parameter is obtained by comprehensive calculation based on the dust participation value, the current attenuation accumulation value and the current fluctuation value.

[0012] Furthermore, the dust participation value is specifically obtained as follows: the number of image contours is compared with zero. If the number of image contours is equal to zero, the dust participation value is assigned to one; if the number of image contours is greater than zero, the dust participation value is assigned to zero.

[0013] Furthermore, the specific method for obtaining the current attenuation accumulation value is as follows: according to the number of current amplitudes, the current amplitudes at different times are calculated for difference, and the current deviation value and the number of current deviation values ​​are obtained; according to the number of current deviation values, the current deviation values ​​are summed and calculated to obtain the current attenuation accumulation value.

[0014] Furthermore, the scanning state parameters are specifically obtained as follows: when the dust participation value is one, the alignment start time and the alignment end time are set, the alignment end time and the alignment start time are calculated to obtain the alignment time, the alignment time threshold and the exceed time are set, and the alignment time and the alignment time threshold are compared. If the alignment time is greater than the alignment time threshold, the alignment time and the alignment time threshold are calculated to obtain the difference, and the exceed time is assigned. If the alignment time is less than or equal to the alignment time threshold, the exceed time is assigned to one. In the time series, the average value of the difference between the voltage amplitudes at different times is taken to obtain the voltage relaxation value. The voltage amplitude is calculated according to the number of voltage amplitudes by the variance method to obtain the voltage fluctuation value, which reflects that the reflected infrared light intensity of the white barcode and the black barcode tends to be blurred. The scanning state parameters are obtained by performing a comprehensive calculation based on the exceed time, the voltage relaxation value and the voltage fluctuation value. Wherein, MC represents the scanning state parameter, CS represents the overtime, HZ represents the voltage relaxation value and is not zero, and YZ represents the voltage fluctuation value and is not zero.

[0015] Furthermore, the voltage relaxation value is specifically obtained as follows: the voltage values ​​at different times are subjected to difference calculations based on the number of voltage amplitudes to obtain the voltage deviation value and the number of voltage deviation values; the voltage deviation values ​​are summed and averaged based on the number of voltage deviation values ​​to obtain the voltage relaxation value.

[0016] Furthermore, the specific steps of matching the barcode data with the patient information data are: converting the voltage amplitude of the barcode data into a coding form, recorded as the inspection code, and the patient information data is also in a coding form, recorded as the initial code, and matching the inspection code and the initial code in sequence. When the inspection code and the initial code are successfully matched, an electronic cloud film and report are obtained.

[0017] Furthermore, the data acquisition module, the data preprocessing module, the data storage module and the central computing and processing module: the data storage module is used to store patient information data; the data acquisition module is used to collect image data, dust data and barcode data in real time; the data preprocessing module is used to preprocess the image data, dust data and barcode data; the central computing and processing module is used to perform comprehensive calculations on the preprocessed image data, dust data and barcode data to obtain a scanning abnormality factor, and analyze whether the scanning is abnormal based on the scanning abnormality factor. If the scanning is normal, the barcode data is matched with the patient information data to obtain an electronic cloud film and a report, and the process ends. If the scanning is abnormal, the image data and the barcode data are comprehensively calculated through a data multi-source matching algorithm to obtain patient identity repair data, which restores the patient's real identity information. Then, the patient identity repair data is matched with the patient information data to obtain an electronic cloud film and a report, and the process ends.

[0018] Beneficial effects

[0019] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0020] 1. Through multi-source data collection and comprehensive calculation, the system can accurately identify the impact of dust on scanning. When dust causes scanning abnormalities, it automatically triggers the data multi-source matching algorithm to restore patient identity information, avoiding the need for patients to manually enter information due to dust interference, significantly shortening data synchronization time, and improving patients' efficiency in obtaining electronic cloud films and reports.

[0021] 2. By utilizing the collaborative work of two types of sensors, the system constructs a scanning status assessment model based on multiple parameters. When scanning anomalies are detected, it uses dual verification of image contour features and barcode encoding to restore patient identity, significantly improving the success rate of data synchronization under dust interference and resolving issues with incorrect or interrupted identity information matching.

[0022] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This invention is a flow chart of a data synchronization method based on electronic cloud films and reports.

[0024] Figure 2 This invention: a structural diagram of a data synchronization system based on electronic cloud film and report. DETAILED DESCRIPTION

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0026] It should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0027] Example 1:

[0028] like Figure 1 As shown, an embodiment of the present invention provides a data synchronization method based on electronic cloud film and report, which includes the following specific steps:

[0029] Step 1: Store the patient's registered identity information into the database to obtain the patient information data;

[0030] Step 2: Start collecting image data in real time through the camera. The camera is aimed at the barcode report in the patient's hand to facilitate the collection of the image outline of the barcode;

[0031] Real-time dust data is collected through an infrared photoelectric reflective sensor. The infrared photoelectric reflective sensor is placed inside the self-service inspection machine and emits infrared light that penetrates the transparent glass of the barcode scanning port of the self-service inspection machine. If there is a patient in front of the self-service inspection machine, the infrared light will shine on the inspection form with the barcode. If there is no patient in front of the self-service inspection machine, the infrared light will shine on the table at a specific position of the self-service inspection machine, so that the infrared light will shine on the standard reference object to generate standard reflected infrared light and receive it, thereby collecting the standard reflected light intensity and converting the standard reflected light intensity into the state of the current signal. Since dust will adhere to or float on the outside of the transparent glass and enter the self-service inspection machine through the gaps in the self-service inspection machine and adhere to or float on the inside of the transparent glass, the impact of dust is reflected according to the state of the current signal. Therefore, the dust data includes current amplitude and current amplitude quantity;

[0032] Barcode data is collected in real time through a charge-coupled device sensor, which is also placed in the self-service inspection machine. It receives reflected infrared light that penetrates the transparent glass to collect the barcode on the patient report. Since the infrared photoelectric reflective sensor can not only emit infrared light but also receive reflected infrared light, the charge-coupled device sensor only receives reflected infrared light. That is, the infrared photoelectric reflective sensor and the charge-coupled device sensor cooperate with each other. According to the different intensities of the infrared light reflected by the black and white barcodes on the barcode report, the charge-coupled device sensor receives the intensity of the reflected infrared light and converts it into a voltage state. The voltage state reflects the matching accuracy of the barcode, so the barcode data includes the voltage amplitude and the number of voltage amplitudes.

[0033] Step 3: De-noising the image data helps reduce pixel interference and improve image clarity. Filtering the dust data and barcode data helps preserve their true signal characteristics.

[0034] Step 4: Process the image data through image contour segmentation algorithm and image contour tracking algorithm. Image contour segmentation algorithm: For example, Sobel algorithm, first convert the image data into grayscale image to simplify calculation, then use 3×3 convolution kernel in horizontal and vertical directions to convolve respectively to obtain horizontal and vertical gradient matrices; then calculate the gradient amplitude and direction, the former determines the edge, and the latter determines the edge extension direction; finally, through threshold binarization, mark the pixels above the threshold as contours, and finally obtain the image contour. The image contour includes the number of pixels and the brightness value of the pixels. Image contour tracking algorithm: For example, Lucas-Kanade optical flow method, based on the assumption that the brightness values ​​of pixels in adjacent frames are constant, establish the optical flow constraint equation, calculate the spatial and temporal gradients through Sobel algorithm and frame difference, assume that the neighborhood motion is consistent to construct an overdetermined equation group and solve the optical flow velocity by least squares method, finally select feature points such as corner points for tracking and position update, so as to track the image contour;

[0035] Standardization processing is performed based on the image contour, dust data and barcode data, which helps to eliminate the dimension of the image contour, dust data and barcode data, and converts numerical values ​​of different orders of magnitude into a unified numerical range, and performs comprehensive calculations to obtain dust impact parameters and scanning state parameters. Normalization processing is performed based on the dust impact parameters and scanning state parameters, which helps to eliminate the dimension of the dust impact parameters and scanning state parameters, and converts numerical values ​​of different orders of magnitude into values ​​between zero and one, and performs comprehensive calculations to obtain scanning anomaly factors. The scanning anomaly factors are used to analyze whether the scanning is abnormal. If the scanning is normal, the barcode data is matched with the patient information data to obtain an electronic cloud film and report, and this process ends. If the scanning is abnormal, the image data and the barcode data are comprehensively calculated through a data multi-source matching algorithm to obtain patient identity repair data, which restores the patient's true identity information. The patient identity repair data is then matched with the patient information data to obtain an electronic cloud film and report, and this process ends.

[0036] The specific method of analyzing whether a scan is abnormal based on the scan abnormality factor is as follows:

[0037] The scan anomaly threshold is set through historical experiments. The scan anomaly threshold is used as a standard to measure whether the scan is abnormal. The scan anomaly factor is compared with the scan anomaly threshold. If the scan anomaly factor is less than or equal to the scan anomaly threshold, the scan is analyzed to be normal. If the scan anomaly factor is greater than the scan anomaly threshold, the scan is analyzed to be abnormal.

[0038] The specific method of obtaining the scanning anomaly factor is as follows:

[0039] SY=(HC+k)×MC;

[0040] Among them, SY represents the scanning abnormality factor, which reflects whether the scanning is abnormal; HC represents the dust impact parameter, which reflects whether the dust affects the scanning; MC represents the scanning status parameter, which reflects the status of the scanned barcode data; k represents a positive real number in the range of zero to one, to avoid the dust impact parameter being zero, which causes the scanning abnormality factor to also be zero.

[0041] The specific method for obtaining dust impact parameters is as follows:

[0042] The dust participation value is set according to the number of image contours. After the infrared photoelectric reflective sensor emits infrared light, the infrared light penetrates the transparent glass and illuminates the table at a specific position of the self-service inspection machine, causing the emitted infrared light to be reflected to obtain reflected infrared light. This reflected infrared light then penetrates the transparent glass and is received by the infrared photoelectric reflective sensor to obtain the intensity of this reflected infrared light. However, when the patient aligns the self-service inspection report with the transparent glass, the intensity of the infrared light irradiated thereon will change, so that the infrared photoelectric reflective sensor that receives the reflected infrared light cannot accurately identify the influence of dust. Therefore, the timing of dust detection is adjusted by the dust participation value, that is, when the patient aligns the self-service inspection report with the transparent glass, dust detection is not performed to avoid inaccurate detection. When the patient does not align the self-service inspection report with the transparent glass, dust detection is performed to maintain detection accuracy.

[0043] When dust accumulates more on the transparent glass, it will cause more scattering of infrared light, that is, less reflected infrared light will return along the original path, so the current amplitude will be weaker. Therefore, according to the change of current amplitude in time series, the accumulated value of current attenuation is obtained;

[0044] When dust drifts more frequently on the original path of infrared light, the intensity of infrared light fluctuates due to the scattering of infrared light by dust. Therefore, the current fluctuation value is calculated based on the current amplitude and the number of current amplitudes using the variance method.

[0045] The dust impact parameter is obtained by comprehensive calculation based on the dust participation value, current attenuation accumulation value and current fluctuation value;

[0046] HC=CZ×(RZ+BZ);

[0047] Among them, HC represents the dust impact parameter, which reflects whether dust affects the scan; CZ represents the dust participation value, which is used to adjust the existence of the dust impact parameter; RZ represents the current attenuation accumulation value, which reflects the degree of dust accumulation on the transparent glass and the degree of current attenuation caused by it; BZ represents the current fluctuation value, which reflects the frequency of dust movement on the infrared light path and the fluctuation of the current.

[0048] The specific method of obtaining dust participation value is as follows:

[0049] The number of image contours is compared with zero. If the number of image contours is equal to zero, it means that no patient blocks the infrared light from irradiating the table path at a specific position of the self-service inspection machine. The dust participation value is assigned to one. That is, when the dust participation value is one, the dust impact parameter is reflected by the current fluctuation value and the current attenuation accumulation value. If the number of image contours is greater than zero, it means that a patient blocks the infrared light from irradiating the table path at a specific position of the self-service inspection machine. The dust participation value is assigned to zero. That is, when the dust participation value is zero, the dust impact parameter is also zero, indicating that the influence of dust is not considered at this time, and only the scanning status parameters or scanning abnormality factors are considered.

[0050] The specific method of obtaining the current attenuation accumulation value is as follows:

[0051] The current amplitudes at different moments are calculated for difference according to the number of current amplitudes to obtain a current deviation value and the number of current deviation values; the current deviation values ​​are summed according to the number of current deviation values ​​to obtain a current attenuation accumulation value;

[0052]

[0053] Among them, RZ represents the current attenuation accumulation value, reflecting the degree of current attenuation, m represents the number of current deviation values, DP i Represents the i-th current deviation value. The larger the current deviation value, the weaker the current.

[0054] The specific method for obtaining the current deviation value is as follows:

[0055] DP=LF j -LF j+1 ;

[0056] Among them, DP represents the current deviation value, LF j+1 Indicates the current amplitude at the j+1th moment, LF j It represents the current amplitude at the jth moment. Since the current amplitude gradually decreases with the passage of time, the current deviation value is positive.

[0057] The specific method of obtaining the current fluctuation value is as follows:

[0058] The current amplitudes are summed and averaged according to the number of current amplitudes to obtain the current amplitude mean, which is used as a standard for measuring the current amplitude fluctuation. The current amplitudes are squared with the current amplitude mean to reflect the fluctuation deviation of each current amplitude from the current amplitude mean. The current amplitudes are then summed and averaged according to the number of current amplitudes to obtain the current fluctuation value, which reflects the overall current fluctuation.

[0059]

[0060] Among them, BZ represents the current fluctuation value, reflecting the fluctuation of current, n represents the number of current amplitudes, LF j represents the jth current amplitude.

[0061] The specific method of obtaining the scanning status parameters is as follows:

[0062] When the dust participation value is one, the alignment start time and alignment end time are set. The alignment start time indicates the time when the patient aligns the self-service examination report sheet with the transparent glass, and the alignment end time indicates the time until the patient removes the self-service examination report sheet. The alignment end time and the alignment start time are calculated by difference to obtain the alignment time, and the alignment time threshold and the exceed time are set. The alignment time threshold indicates the time when the patient successfully scans and removes the self-service examination report sheet under normal circumstances. The alignment time is compared with the alignment time threshold. If the alignment time is greater than the alignment time threshold, it indicates that the scan is abnormal, and the alignment time and the alignment time threshold are calculated by difference and assigned to the exceed time. If the alignment time is less than or equal to the alignment time threshold, it indicates that the scan is normal, and the exceed time is assigned to one, indicating that the exceed time has no effect.

[0063] Under normal circumstances, the black and white barcodes on the self-service examination report have different intensities of reflected infrared light. The black barcode absorbs light strongly, and the corresponding reflected infrared light intensity is weak, while the white barcode absorbs light weakly, and the corresponding reflected infrared light intensity is strong. Patient information data is obtained based on the order of the reflected infrared light intensity of each black barcode and white barcode. However, the granular structure of dust will form a light reflection and scattering interface. At the same time, the reflective properties of the dust itself will weaken the black barcode's absorption efficiency of the incident infrared light, resulting in poor attenuation efficiency of the reflected infrared light. Therefore, under the influence of dust, the reflected infrared light of the corresponding black barcode is enhanced. Similarly, the white barcode originally absorbs light weakly and reflects infrared light strongly, but due to the scattering of dust, the reflected infrared light of the white barcode is weakened. Therefore, the difference in the reflected infrared light intensity between the white barcode and the black barcode is reduced, and the fluctuation trend tends to be gentle. In the time series, the voltage amplitude difference at different times is summed and averaged to obtain the voltage relaxation value. The smaller the voltage relaxation value, the more abnormal the scan.

[0064] The voltage amplitude is calculated based on the number of voltage amplitudes using the variance method to obtain the voltage fluctuation value, which reflects that the reflected infrared light intensity of the white barcode and the black barcode tends to be blurred;

[0065] The scanning state parameters are obtained by performing comprehensive calculation based on the exceeding time, voltage relief value and voltage fluctuation value;

[0066]

[0067] Among them, MC represents the scanning status parameter, CS represents the time limit, which means that the longer the scanning time, the worse the scanning status; HZ represents the voltage relaxation value, which is not zero. The smaller the voltage relaxation value, the more affected by dust, the smaller the difference in intensity of the reflected infrared light corresponding to the black barcode and the white barcode, and the worse the scanning status; YZ represents the voltage fluctuation value, which is not zero. The smaller the voltage fluctuation, the more affected the reflected infrared light corresponding to the black barcode and the white barcode is by dust, and the worse the scanning status.

[0068] The specific method for obtaining the voltage relief value is as follows:

[0069] The voltage values ​​at different times are calculated for difference according to the number of voltage amplitudes to obtain a voltage deviation value and the number of voltage deviation values. The voltage deviation values ​​are summed and averaged according to the number of voltage deviation values ​​to obtain a voltage relief value.

[0070]

[0071] Among them, HZ represents the voltage relaxation value, t represents the number of voltage deviation values, YP r Represents the rth voltage deviation value.

[0072] The specific method for obtaining the voltage fluctuation value is as follows:

[0073] The voltage amplitudes are summed and averaged according to the number of voltage amplitudes to obtain the mean voltage amplitude value, which is used as a standard for measuring voltage amplitude fluctuation. The square of the difference between the voltage amplitude and the mean voltage amplitude is calculated in turn to reflect the fluctuation deviation of each voltage amplitude from the mean voltage amplitude. The voltage amplitudes are then summed and averaged according to the number of voltage amplitudes to obtain the voltage fluctuation value, which reflects the overall voltage fluctuation.

[0074]

[0075] Among them, YZ represents the voltage fluctuation value, reflecting the voltage fluctuation, h represents the number of voltage assignments, LF u Represents the u-th voltage amplitude.

[0076] The specific steps to match barcode data with patient information data are:

[0077] Since different voltage amplitudes correspond to different codes, the barcode on a self-service examination report corresponds to a unique code. Therefore, the voltage amplitude of the barcode data is converted into a coding form, recorded as the examination code, and the patient information data is also in a coding form, recorded as the initial code. The examination code and the initial code are matched with the same code in sequence. When the examination code and the initial code are successfully matched, the electronic cloud film and report are obtained, and then the patient identity information, electronic cloud film and report are successfully synchronized.

[0078] The specific methods of patient identity repair data are as follows:

[0079] Set a standard barcode contour, sum and calculate the number of pixels in the standard barcode contour to obtain the standard barcode contour area, sum and calculate the number of pixels in each image contour to obtain the image contour area, set a fault tolerance threshold, calculate the difference between the image contour area and the standard barcode contour area to obtain the fault tolerance value, compare the fault tolerance value with the fault tolerance threshold, if the fault tolerance value is within the fault tolerance threshold, it means that a certain error between the image contour area and the standard barcode contour area is allowed, but it does not affect the image contour as a standard barcode contour, if the fault tolerance value is outside the fault tolerance threshold, it means that the error between the image contour and the standard barcode contour is large, and the image contour is not a standard barcode contour, set contour coding, which is used to correspond through contour and coding, count the image contour of the barcode in the order of the barcode, and obtain a set of standard barcode contours, traverse the contour coding according to a set of standard barcode contours, and obtain the encoding of this barcode, which is recorded as patient identity repair data.

[0080] like Figure 2 Shown: A data synchronization system based on electronic cloud film and report, comprising:

[0081] Data storage module: used to store patient information data;

[0082] Data acquisition module: used to collect image data, dust data and barcode data in real time;

[0083] Data preprocessing module: used to preprocess image data, dust data and barcode data;

[0084] Central computing and processing module: used to perform comprehensive calculations on the pre-processed image data, dust data, and barcode data to obtain a scanning anomaly factor, and analyze whether the scan is abnormal based on the scanning anomaly factor. If the scan is normal, the barcode data is matched with the patient information data to obtain an electronic cloud film and report, and this process ends. If the scan is abnormal, the image data and barcode data are comprehensively calculated through a data multi-source matching algorithm to obtain patient identity restoration data, which restores the patient's true identity information. The patient identity restoration data is then matched with the patient information data to obtain an electronic cloud film and report, and this process ends.

[0085] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A data synchronization method based on electronic cloud films and reports, characterized by: The specific steps include: Step 1: Store patient information data; Step 2: Start collecting image data, dust data, and barcode data in real time; Step 2: Preprocess the image data, dust data and barcode data; Step 4: Perform comprehensive calculation on the pre-processed image data, dust data and barcode data to obtain the scanning abnormality factor. Analyze whether the scan is abnormal based on the scanning abnormality factor. If the scan is normal, match the barcode data with the patient information data to obtain the electronic cloud film and report, and end this process. If the scan is abnormal, perform comprehensive calculation on the image data and barcode data through the data multi-source matching algorithm to obtain the patient identity repair data, which restores the patient's true identity information. Then, match the patient identity repair data with the patient information data to obtain the electronic cloud film and report, and end this process.

2. The data synchronization method based on electronic cloud film and report according to claim 1, characterized in that: The specific method of analyzing whether the scan is abnormal based on the scan abnormality factor is as follows: Set a scan anomaly threshold and compare the scan anomaly factor with the scan anomaly threshold. If the scan anomaly factor is less than or equal to the scan anomaly threshold, the scan is analyzed to be normal. If the scan anomaly factor is greater than the scan anomaly threshold, the scan is analyzed to be abnormal.

3. The data synchronization method based on electronic cloud film and report according to claim 2, characterized in that: The specific method of obtaining the scanning abnormality factor is as follows: The image data is processed by an image contour segmentation algorithm and an image contour tracking algorithm to obtain the image contour. The image contour, dust data, and barcode data are standardized and comprehensively calculated to obtain dust impact parameters and scanning status parameters. The dust impact parameters and scanning status parameters are normalized and comprehensively calculated to obtain scanning anomaly factors. SY=(HC+k)×MC; Wherein, SY represents the scanning abnormality factor, HC represents the dust impact parameter, MC represents the scanning state parameter, and k represents a positive real number.

4. The data synchronization method based on electronic cloud film and report according to claim 3, characterized in that: The specific method of obtaining the dust impact parameter is as follows: A dust participation value is set according to the number of image contours. The dust data includes the current amplitude and the current amplitude quantity. The barcode data includes the voltage amplitude and the voltage amplitude quantity. According to the change of the current amplitude in the time series, the current attenuation accumulation value is obtained. The current fluctuation value is obtained by calculation based on the variance method and the current amplitude and the current amplitude quantity. The dust impact parameter is obtained by comprehensive calculation based on the dust participation value, the current attenuation accumulation value and the current fluctuation value.

5. The data synchronization method based on electronic cloud film and report according to claim 4, characterized in that: The specific method of obtaining the dust participation value is as follows: The number of image contours is compared with zero. If the number of image contours is equal to zero, the dust participation value is assigned to one. If the number of image contours is greater than zero, the dust participation value is assigned to zero.

6. The data synchronization method based on electronic cloud film and report according to claim 4, characterized in that: The specific method of obtaining the current decay accumulation value is as follows: The current amplitudes at different moments are calculated for difference according to the number of current amplitudes to obtain a current deviation value and the number of current deviation values. The current deviation values ​​are summed according to the number of current deviation values ​​to obtain a current attenuation accumulation value.

7. The data synchronization method based on electronic cloud film and report according to claim 3, characterized in that: The specific method of obtaining the scanning status parameters is as follows: When the dust participation value is one, the alignment start time and the alignment end time are set, and the alignment end time is calculated as the difference between the alignment start time to obtain the alignment time. The alignment time threshold and the exceed time are set, and the alignment time is compared with the alignment time threshold. If the alignment time is greater than the alignment time threshold, the alignment time and the alignment time threshold are calculated as the difference and assigned to the exceed time. If the alignment time is less than or equal to the alignment time threshold, the exceed time is assigned to one. In the time series, the average value of the voltage amplitude difference at different times is taken to obtain the voltage relaxation value. The voltage amplitude is calculated according to the number of voltage amplitudes using the variance method to obtain the voltage fluctuation value, which reflects that the reflected infrared light intensity of the white barcode and the black barcode tends to be blurred. The scanning state parameter is obtained by comprehensive calculation based on the exceed time, voltage relaxation value and voltage fluctuation value. Wherein, MC represents the scanning state parameter, CS represents the overtime, HZ represents the voltage relaxation value and is not zero, and YZ represents the voltage fluctuation value and is not zero.

8. The data synchronization method based on electronic cloud film and report according to claim 7, characterized in that: The specific method for obtaining the voltage relief value is as follows: The voltage values ​​at different times are calculated for difference according to the number of voltage amplitudes to obtain the voltage deviation value and the number of voltage deviation values. The voltage deviation values ​​are summed and averaged according to the number of voltage deviation values ​​to obtain the voltage relief value.

9. The data synchronization method based on electronic cloud film and report according to claim 1, characterized in that: The specific steps of matching the barcode data with the patient information data are: The voltage amplitude of the barcode data is converted into a coding form, recorded as the inspection code, and the patient information data is also in a coding form, recorded as the initial code. The inspection code and the initial code are matched with the same code in sequence. When the inspection code and the initial code are successfully matched, the electronic cloud film and report are obtained.

10. A data synchronization system based on electronic cloud films and reports, used to implement a data synchronization method based on electronic cloud films and reports according to any one of claims 1 to 9, characterized in that: The system includes: a data acquisition module, a data preprocessing module, a data storage module and a central computing and processing module: The data storage module is used to store patient information data; The data acquisition module is used to collect image data, dust data and barcode data in real time; The data preprocessing module is used to preprocess the image data, dust data and barcode data; The central computing and processing module is used to perform comprehensive calculations on the pre-processed image data, dust data, and barcode data to obtain a scanning abnormality factor, and analyze whether the scanning is abnormal based on the scanning abnormality factor. If the scanning is normal, the barcode data is matched with the patient information data to obtain an electronic cloud film and a report, and this process ends. If the scanning is abnormal, the image data and the barcode data are comprehensively calculated using a data multi-source matching algorithm to obtain patient identity restoration data, which restores the patient's true identity information. The patient identity restoration data is then matched with the patient information data to obtain an electronic cloud film and a report, and this process ends.

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